ShayanShamsi/IOL-AI

TEXT GENERATIONConcurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 10, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Qwen3-4B is a 4 billion parameter causal language model developed by Qwen, featuring a native context length of 32,768 tokens, extendable to 131,072 tokens with YaRN scaling. This model uniquely supports seamless switching between a 'thinking mode' for complex reasoning, math, and coding, and a 'non-thinking mode' for efficient general-purpose dialogue. It demonstrates enhanced reasoning capabilities, superior human preference alignment for creative tasks, and strong agentic abilities with multilingual support for over 100 languages.

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Qwen3-4B: A Versatile Language Model with Adaptive Thinking Capabilities

Qwen3-4B is a 4 billion parameter causal language model from the Qwen series, designed for advanced reasoning, instruction-following, and agentic tasks. It stands out by offering a unique dual-mode operation, allowing users to switch between a 'thinking mode' for complex logical reasoning, mathematics, and code generation, and a 'non-thinking mode' for efficient, general-purpose dialogue. This adaptability ensures optimal performance across diverse scenarios.

Key Capabilities

  • Adaptive Thinking Modes: Seamlessly switch between a reasoning-focused mode and an efficient dialogue mode, either explicitly or dynamically via user prompts (/think, /no_think).
  • Enhanced Reasoning: Demonstrates significant improvements in mathematical problem-solving, code generation, and commonsense logical reasoning, surpassing previous Qwen models.
  • Superior Alignment: Excels in creative writing, role-playing, multi-turn conversations, and instruction following, providing a more natural and engaging user experience.
  • Agentic Expertise: Offers precise integration with external tools, achieving leading performance in complex agent-based tasks among open-source models.
  • Multilingual Support: Supports over 100 languages and dialects with strong capabilities for multilingual instruction following and translation.
  • Extended Context Window: Natively handles up to 32,768 tokens, with support for up to 131,072 tokens using YaRN scaling for processing long texts.

Good for

  • Applications requiring dynamic reasoning capabilities.
  • Complex problem-solving in math and coding.
  • Creative content generation and engaging conversational AI.
  • Agent-based systems and tool integration.
  • Multilingual applications and translation tasks.

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